Why You Should Be Watching Digital Twins

No, it’s not a new instant messaging tool, an ai-powered virtual assistant, or handheld device. Sure, Apple is going to update the iPhone again and there’s sure to be social network that is tagged as ‘the next Facebook’ but there’s nothing new there. There’ll be gadgets, there’ll be further advances in electric vehicles and smart cities, and for sure Elon Musk is going to do something that will be declared visionary…again.

However, the most important technology trend for 2017 isn’t likely to be something that lights up the front pages of the local newspaper or goes viral one afternoon online. Instead, it is a technology trend that is beginning to change the way in which some of the world’s biggest businesses are doing business, investing in their assets, and managing their companies in a more efficient and effective way.

It’s the concept of the digital twin.

Gartner has named digital twins one of its Top 10 Strategic Technology Trends for 2017 and they’re right – this is an idea and, increasingly, a reality that is transforming the way that big business is working. But what is a digital twin? In simple terms, a digital twin is a digital representation of a physical asset that, thanks to the internet of things (IoT), data gathering and analytics, and modeling, allows an asset owner to understand how to best manage their asset, optimize its maintenance, and predict failures even before they occur.

For industrial companies with hundreds of millions, even many billions invested in assets, a digital twin program can help determine when an asset needs repair, if an asset is being over-used or taxed by poor management, and identify ways to extend the lifespan of the asset to extract the maximum useful life relative to the significant investment made in that asset.

GE is one company that has embraced digital twins and Colin Parris, Vice President at GE Software Research, defined the concept during an interview with ARC as “a living model of something that delivers a business outcome”. The BBC recently reported on the success of GE’s program for the expensive jet engines the company manufactures and sells to the world’s biggest airlines. Anthony Dean, head of combustion systems at GE’s Global Research Center, explained to the BBC that, as each jet engine is built, it is equipped with about 100 sensors that measure its essential parts.

For example, “The pressure and temperature at the exit of the compressor is a key indicator of the health of the compressor,” says Dean. They also keep an eye on the exhaust temperature, the speed at which the turbines are spinning, and how far the fuel valve opens.

As the BBC further explains, GE can “compare the data gathered by the sensors to the engine’s digital twin (which can be put through the same paces that the engine experiences as it takes off, flies through different types of weather, and undergoes regular wear and tear). If the two data sets don’t match up, then the engine needs servicing because something undesirable is going on.”

In other words, GE’s digital twin program for jet engines helps it make optimal decisions regarding the management of these assets. These optimal decisions in turn lead to faster, safer flights for consumers, and improved efficiency and profits for the airlines that own the engines.

But while GE might be among the handful of companies building jet engines, they are not the only company developing digital twins. Indeed, when it comes to the most complex industrial contexts and when assets are counted in the tens of thousands instead of hanging two or four to an aircraft wing, the world-leading technology of a business like The CoSMo Company really comes into its own. CoSMo’s unique software and its modeling and simulation approach to complex systems allow businesses to model the most complex of industrial environments, the multitude of assets within that environment, the polices and maintenance plans for those assets, available resources, changing demographics and social factors, and the list goes on. Indeed, where Anthony Dean explained that the typical GE jet engine has some 100 different sensors collecting data, a typical CoSMo model might involve the concurrent assessment and simulation of thousands of different assets, constraints, and resources at once.

Simulating real scenarios using digital representations of a system have and will increasingly improve decision management.

This sort of digital twinning is already helping businesses like RTE (Europe’s largest electricity transmission system operator), SNCF (operator of one of the world’s largest passenger and freight rail networks with more than a billion passenger journeys in 2016), Alstom (a global leader in transport technology and networks), and Veolia (one of the world’s leading water and essential services utilities) to make optimal decisions in their asset management practices, in their asset investment strategies, and set a course for success with auditable, repeatable, and reliable predictions of the future state of their physical assets and the world in which they will exist.

Digital twins won’t make the front page of Wired magazine, and nor will they steal the show in Las Vegas at CES or be a fixture on the home screen of every teenager’s smartphone.

They will, however, transform the way that business is done, that assets are managed, and that optimal decisions are realized – indeed, as the early success of GE and The CoSMo Company has demonstrated, they already are.

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